qProtein: Exploring\nPhysical Features of Protein Thermostability\nBased on Structural Proteomics

Thermostability, which is essential for the functional\nperformance\nof enzymes, is largely determined by intramolecular physical interactions.\nAlthough many tools have been developed, existing computational methods\nhave struggled to find the universal principles of protein thermostability.\nRecent advancements in structural proteomics have been driven by the\nintroduction of deep neural networks such as AlphaFold2 and ESMFold.\nThese innovations have enabled the characterization of protein structures\nwith unprecedented speed and accuracy. Here, we introduce qProtein,\na Python-implemented workflow designed for the quantitative analysis\nof physical interactions on the scale of structural proteomics. This\nplatform accepts protein sequences as input and produces four structural\nfeatures, including hydrophobic clusters, hydrogen bonds, electrostatic\ninteractions, and disulfide bonds. To demonstrate the use of qProtein,\nwe investigate the structural features related to protein thermostability\nin six glycoside hydrolase (GH) families, comprising a total of 3,811\nprotein structures. Our results indicate that in five enzyme families\n(GH11, GH12, GH5_2, GH10, and GH48), the thermophilic enzymes have\na larger average area of hydrophobic clusters compared to the nonthermophilic\nenzymes within each family. Furthermore, our analysis of the local-structure\nregions reveals that the hydrophobic clusters are predominantly distributed\nin the distal regions of the GH11 enzymes. In addition, the average\nhydrophobic cluster area of the thermophilic enzymes is significantly\nhigher than that of the nonthermophilic enzymes in the distal regions\nof the GH11 enzymes. Therefore, qProtein is a well-suited platform\nfor analyzing the structural features of thermal stability at the\nlevel of structural proteomics. We provide the source code for qProtein\nat https://github.com/bj600800/qProtein, and the web server is available at http://qProtein.sdu.edu.cn:8888.